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1995
ACM

Predicting Application Behavior in Large Scale Shared-memory Multiprocessors

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Predicting Application Behavior in Large Scale Shared-memory Multiprocessors
In this paper we present an analytical-based framework for parallel program performance prediction. The main thrust of this work is to provide a means for treating realistic applications within a single uni ed framework. Our approach is based upon the speci cation of a set of non-linear equations which describe the application, processor con guration, network and memory operations. These equations are solved iteratively since the application execution rate depends on the communication latencies. The iterative solution technique is found to be ecient as it typically requires only few iterations to reach convergence. Our modeling methodology achieves a good balance between ion and accuracy. This is attained by accounting for both time and space dimensions of memory references, while maintaining a simple description of the workload. We demonstrate both the practicality and the accuracy of our approach by comparing predicted results with measurements taken on a commercial multiprocessor ...
Karim Harzallah, Kenneth C. Sevcik
Added 26 Aug 2010
Updated 26 Aug 2010
Type Conference
Year 1995
Where SC
Authors Karim Harzallah, Kenneth C. Sevcik
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